Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
question-generation
License:
Update README.md
Browse files
README.md
CHANGED
@@ -13,12 +13,12 @@ task_ids: question-generation
|
|
13 |
|
14 |
## Dataset Description
|
15 |
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
|
16 |
-
- **Paper:** [
|
17 |
- **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
|
18 |
|
19 |
### Dataset Summary
|
20 |
This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
|
21 |
-
["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](
|
22 |
This is [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) dataset for question generation (QG) task. The split
|
23 |
of train/development/test set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is
|
24 |
compatible with the [leader board](https://paperswithcode.com/sota/question-generation-on-squad11).
|
|
|
13 |
|
14 |
## Dataset Description
|
15 |
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
|
16 |
+
- **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
|
17 |
- **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
|
18 |
|
19 |
### Dataset Summary
|
20 |
This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
|
21 |
+
["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](https://arxiv.org/abs/2210.03992).
|
22 |
This is [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) dataset for question generation (QG) task. The split
|
23 |
of train/development/test set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is
|
24 |
compatible with the [leader board](https://paperswithcode.com/sota/question-generation-on-squad11).
|